| LDR | | 00000nmm u2200205 4500 |
| 001 | | 000000331650 |
| 005 | | 20241119165638 |
| 008 | | 181129s2018 ||| | | | eng d |
| 020 | |
▼a 9780438338753 |
| 035 | |
▼a (MiAaPQ)AAI10931980 |
| 035 | |
▼a (MiAaPQ)cmu:10290 |
| 040 | |
▼a MiAaPQ
▼c MiAaPQ
▼d 248032 |
| 049 | 1 |
▼f DP |
| 082 | 0 |
▼a 629.8 |
| 100 | 1 |
▼a Rodrigues, Jose Jeronimo Moreira. |
| 245 | 10 |
▼a 3D Pose Estimation for Bin-picking: A Data-driven Approach Using Multi-light Images. |
| 260 | |
▼a [S.l.] :
▼b Carnegie Mellon University.,
▼c 2018 |
| 260 | 1 |
▼a Ann Arbor :
▼b ProQuest Dissertations & Theses,
▼c 2018 |
| 300 | |
▼a 113 p. |
| 500 | |
▼a Source: Dissertation Abstracts International, Volume: 80-01(E), Section: B. |
| 500 | |
▼a Includes supplementary digital materials. |
| 500 | |
▼a Advisers: Takeo Kanade |
| 502 | 1 |
▼a Thesis (Ph.D.)--Carnegie Mellon University, 2018. |
| 520 | |
▼a We study the problem of 3D pose estimation of textureless shiny objects from monocular 2D images, for a bin-picking task. The main challenge of dealing with a shiny object comes from the fact that the object appearance largely changes with its p |
| 520 | |
▼a In this thesis, we develop a purely data-driven method to tackle the pose estimation problem. Motivated by photometric stereo, we develop an imaging system with multiple lights to acquire a multi-light image where channels are obtained by varyin |
| 520 | |
▼a Experiments show that the given method can detect and estimate poses of textureless and shiny objects accurately and robustly within half a second. We further compare our approach with the HALCON commercial software, a highly optimized hierarchi |
| 590 | |
▼a School code: 0041. |
| 650 | 4 |
▼a Robotics. |
| 650 | 4 |
▼a Computer science. |
| 650 | 4 |
▼a Computer engineering. |
| 690 | |
▼a 0771 |
| 690 | |
▼a 0984 |
| 690 | |
▼a 0464 |
| 710 | 20 |
▼a Carnegie Mellon University.
▼b Electrical and Computer Engineering. |
| 773 | 0 |
▼t Dissertation Abstracts International
▼g 80-01B(E). |
| 773 | |
▼t Dissertation Abstract International |
| 790 | |
▼a 0041 |
| 791 | |
▼a Ph.D. |
| 792 | |
▼a 2018 |
| 793 | |
▼a English |
| 856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T15001069
▼n KERIS |
| 980 | |
▼a 201812
▼f 2019 |
| 990 | |
▼a 관리자
▼b 관리자 |